Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

      The Matching and Mosaic of the satellite imagery play an essential role in many remote sensing and image processing projects. These techniques must be required in a particular step in the project, such as remotely change detection applications and the study of large regions of interest. The matching and mosaic methods depend on many image parameters such as pixel values in the two or more images, projection system associated with the header files, and spatial resolutions, where many of these methods construct the matching and mosaic manually. In this research, georeference techniques were used to overcome the image matching task in semi automotive method. The decision about the quality of the technique can be considered i

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical

         The aims of the present study are to evaluate the levels of CA19-9 in sera and tissues' homogenate of breast and thyroid benign patients in order to assess its use as an early diagnostic parameter in differentiation between malignant and benign cases. The study was conducted on 8 patients with breast benign tumor and 8 patients with thyroid benign tumor, by the enzyme linked immunosorbent assay (ELISA) technique. The results of CA19-9 levels in sera were (15 ±1.58 and 10.67 ±2.08)U/ml respectively compared with serum CA19-9 levels of control group which was 7.74 ±4.92 U/ml, the results were found to be highly significantly in breast tumor patients and non significantly in thyroid

The tremendous benefits of using cellular phones, which began to increase and unprecedented spread worldwide last decade, were accompanied by harmful effects on the environment due to the increase in electromagnetic radiation (EMR) which be emitted from mobile phone towers. This effect on humans, animals, and plants, which is considered a form of environmental pollution, was sensed by developed countries and Environmental protection organizations. These countries have established restrictions and enacted laws to reduce their negative impact on living beings. The field survey included six major hospitals and 38 schools were distributed over the central neighbourhoods in Al-Najaf city. The results showed that power density (PD) measurement

The expression of MUC5AC has been associated with the loss of the differentiation, TNM system, and nodal metastasis, in many cancers including gastric carcinoma (GC).Objective: To evaluate whether the MUC5AC could be used as a predictor in patients with GC and to assess the correlation between the expression of MUC5AC& the clinicpathological parameters as age, sex, histopathological subtypes, grade and stage of the tumor. This is a retrospective study conducted on 60 randomly selected patients (30 normal vs 30 GC), at the Pathology Department of the Gastroenterology and Hepatology Teaching Hospital&some private laboratories. They were collected and diagnosed during the period 2014-2018. Histological sections were stained with H&E and IHC st

Background: The elimination of the microorganisms from the root canal systems, an important step for the successful root canal treatment. This study was conducted to evaluate the antibacterial effectiveness of the photoactivated disinfection by using the toluidine blue O and a low- energy light emitting diode (LED) lamp . Materials and method: Sixty single rooted extracted teeth were decoronated, instrumented, irrigated, sealed at the apex and contaminated with endodontic anaerobic bacteria for 7 days to form biofilms in prepared root canals. Group I. Twelve teeth were medicated by photosensitizer (toluidine blue O) solution activated by diode lamp (FotoSan; CMS Dental, Copenhagen, Denmark).Group II. Twelve teeth were medicated by the tricr

To determine the potential of gingival crevicular fluid (GCF) volume, E‐cadherin and total antioxidant capacity (TAC) levels to predict the outcomes of nonsurgical periodontal therapy (NSPT) for periodontitis patients.